Vote Intention Polls Research Articles

Institutions, parties and the evolution of electoral preferences

AbstractPolitical institutions and parties define the set of choices faced by voters, and structure the evolution of electoral preferences over the election cycle. While previous research examines the characteristics of institutions, here we consider the influence of political parties. We theorize ways in which they matter to the formation of electoral preferences over the election timeline, and also how these relate to institutional features. Our analysis simultaneously assesses the influence of different system‐ and party‐level variables on the dynamic structure of voters’ preferences in legislative elections using a dataset of 27,357 vote intention polls in 26 countries since 1942, covering 231 discrete electoral cycles and encompassing 208 political parties. The results indicate that electoral institutions and parties are both important, but the characteristics of parties matter most of all, and effectively mediate institutional influences. These results have implications for the effects of election campaigns, the prediction of election outcomes, and party behavior itself.

Reporting the polls: the quality of media reporting of vote intention polls in the Netherlands

This article examines the media coverage of vote intention polls in the Netherlands. We assess whether the quality of media reporting on polls depends on the availability of information regarding the quality in pollster’s reports. Our analysis of the quality looks at three different quality measures: (1) mentioning WAPOR items, such as field dates, sampling method, and polling method, (2) mentioning the margin of error, and (3) the correct interpretation of (in)significant changes and differences. The Netherlands provides an interesting case, because there is variation over time and across pollsters in the way they report their polls as well as the increased popularity of a polling aggregator. Our findings indicate that the overall quality of Dutch coverage of polls is low. When a pollster mentions the margin of error in its report, media reports on that poll are more likely to include this information and to correctly interpret the significance of differences between two parties. This effect is particularly visible when the pollster provides uncertainty intervals in its headline figures.

Pollster problems in the 2016 US presidential election: vote intention, vote prediction

In recent US presidential elections, there has been considerable focus on how well public opinion can forecast the outcome, and 2016 proved no exception. Pollsters and poll aggregators regularly offered numbers on the horse-race, usually pointing to a Clinton victory, which failed to occur. We argue that these polling assessments of support were misleading for at least two reasons. First, Trump voters were sorely underestimated, especially at the state level of polling. Second, and more broadly, we suggest that excessive reliance on non-probability sampling was at work. Here we present evidence to support our contention, ending with a plea for consideration of other methods of election forecasting that are not based on vote intention polls.

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.

Election forecasting: Too far out?

We consider two criteria for evaluating election forecasts: accuracy (precision) and lead (distance from the event), specifically the trade-off between the two in poll-based forecasts. We evaluate how much “lead” still allows prediction of the election outcome. How much further back can we go, supposing we tolerate a little more error? Our analysis offers estimates of the “optimal” lead time for election forecasts, based on a dataset of over 26,000 vote intention polls from 338 elections in 44 countries between 1942 and 2014. We find that optimization of a forecast is possible, and typically occurs two to three months before the election, but can be influenced by the arrangement of political institutions. To demonstrate how our optimization guidelines perform in practice, we consider recent elections in the UK, the US, and France.

The electoral cycle effect in parliamentary democracies

AbstractDoes government party support decline in a monotonic fashion throughout the legislative cycle or do we observe a u-shaped “electoral cycle effect”? Moving beyond the study of midterm election results, this is the first comparative study to assess the cyclical pulse of government party support in parliamentary democracies based on voting intention polls from 171 cycles in 22 countries. On average, government parties lose support during the first half of the electoral cycle, but at most partially recover from their initial losses. Under single-party government and when prime ministers control cabinet dissolution, support tends to follow the previously assumed u-shaped pattern more strongly. Finally, we find that government parties hardly recover from early losses since the 2000s.

FORECASTING ELECTIONS: DO PREDICTION MARKETS TELLS US ANYTHING MORE THAN THE POLLS?

Election forecasting is an expanding domain within political science, moving from the outer edges (as a novelty pursued by a few ‘quants’) toward the mainstream of the discipline. Amongst the most high profile of election forecasting techniques are prediction markets and vote-intention polls. While the weight of scholarly opinion appears to favour prediction markets over polls for election forecasting, there remain challengers and critics. 
 This article joins with the challengers and the critics, looking at whether this ‘horse race’ competition between election forecasting approaches is valid. Using data from the 2013 Australian federal election, we conclude such comparisons-of-forecasts are misplaced in the Australian context, as prediction markets and vote-intention polls appear to be independent of each other given information from one appears to have no impact on the other.

YES or NO: Predicting the 2015 GReferendum results using Google Trends

We examine the possibility of predicting the 2015 Greek Referendum results by analyzing data from Google Trends on the ‘YES’ and ‘NO’ search terms. Our analysis shows that, despite the voting intention polls of the YES and NO votes being marginally one above the other throughout the prevoting period, the NO hits are clearly and every day above the YES ones, with statistically significant evidence. By analyzing data from Google Trends, we calculate a valid approximation of the final result, thus contributing to the discussion of using Google Trends as an elections' results prediction tool in the future.

From polls to votes to seats: Forecasting the 2015 British general election

This paper develops a three-stage method to forecast parliamentary election results from vote preferences in British opinion polls: (1) adjusting and aggregating vote-intentions from different polling organizations; (2) forecasting how public support for parties will change in the period before election day; and (3) translating, through simulations, the forecast of election day vote shares into seat totals while incorporating constituency-level information, including local vote-intention polls. Overall, this approach seeks to combine relevant national, regional and local information, and uncertainty about that information, to better reflect the fragmentation and diversity of political contexts found in the new era of five/six-party British politics.

Vote expectations at the next level. Trying to predict vote shares in the 2013 German federal election by polling expectations

We add to the literature on citizen forecasting by examining the 2013 German federal election and, for the first time, trying to predict vote shares. A random sample of voters was asked to predict the vote shares for each party in telephone interviews. We examine the accuracy of individuals' expectations and analyze the influence of wishful thinking and published vote intention polls on voters' expectations. Individual forecasts are aggregated, assuming a wise crowd will make a precise forecast. Expectations do not yield a forecast of satisfactory accuracy and they are inferior to vote intention polls. High-ability subgroups do not yield better forecasts than the whole sample. Issues of sampling and measurement are addressed. We conclude that asking voters to predict eight interdependent vote shares is probably too difficult a task.

The Timeline of Elections: A Comparative Perspective

How do voter preferences come into focus over the electoral cycle in different countries? Do they evolve in patterned ways? Does the evolution vary across countries? This article addresses these issues. We consider differences in political institutions and how they might impact voter preferences over the course of the election cycle. We then outline an empirical analysis relating support for parties or candidates in pre‐election polls to their final vote. The analysis relies on over 26,000 vote intention polls in 45 countries since 1942, covering 312 discrete electoral cycles. Our results indicate that early polls contain substantial information about the final result but that they become increasingly informative over the election cycle. Although the degree to which this is true varies across countries in important and understandable ways given differences in political institutions, the pattern is strikingly general.

FORECASTING ELECTIONS: DO PREDICTION MARKETS TELLS US ANYTHING MORE THAN THE POLLS?

Election forecasting is an expanding domain within political science, moving from the outer edges (as a novelty pursued by a few ‘quants’) toward the mainstream of the discipline. Amongst the most high profile of election forecasting techniques are prediction markets and vote-intention polls. While the weight of scholarly opinion appears to favour prediction markets over polls for election forecasting, there remain challengers and critics. This article joins with the challengers and the critics, looking at whether this ‘horse race’ competition between election forecasting approaches is valid. Using data from the 2013 Australian federal election, we conclude such comparisons-of-forecasts are misplaced in the Australian context, as prediction markets and vote-intention polls appear to be independent of each other given information from one appears to have no impact on the other.

Polls and the Vote in Britain

Little is known about the evolution of electoral sentiment over British election cycles. How does party support converge on the eventual election outcome? Do preferences evolve in a patterned and understandable way? What role does the official election campaign period play? In this article, we begin to address these issues. We outline an empirical analysis relating poll results over the course of the election cycle and the final vote for the three main political parties. Then we examine the relationship relying on vote intention polls for the seventeen British general elections between 1950 and 2010. Predictably, polls become increasingly informative about the vote over the election cycle. More surprisingly, early polls contain substantial information about the final outcome, much more than we see in presidential and congressional elections in the US. The final outcome in Britain comes into focus over the long campaign and is to a large extent in place well before the official election campaign begins. The findings are understandable, we think, but raise other questions, which we begin to consider in a concluding section.

Predicting Elections: A ‘Wisdom of Crowds’ Approach

Opinion polls are the currency of politics. They are used by media organisations to evaluate the performance of governments, and by governments and political parties to test the policies that shape manifestos and reform agendas. But opinion polls all rely on one thing - asking people how they themselves intend to vote - and, too often, classical opinion research techniques fail to confront the issues that underpin inaccuracy. In the UK and in many other countries around the world, their performance over the past 20 years has ranged from excellent to disastrous.1 The ‘Wisdom of Crowds’ concept turns conventional predictions on their head. It assumes that any crowd that conforms to a core set of principles is capable of delivering a more accurate prediction than the smartest people within it. This paper tests this proposition within the context of actual elections in the UK, showing that the Wisdom of Crowds approach used by ICM Research at the 2010 general election would have produced the most accurate final pre-election prediction. It also shows that a Wisdom approach to regular vote intention tracking produces an interesting complement to classically conducted vote intention polls. Or, if one were to be bold, a competitor to them.

Forecasting the 2012 French presidential election: Comparing vote function simulations and vote intention polls

In this article, we build a pooled time-series vote function for the 2012 French presidential election both at regional and national levels, taking into account our 2002 and 2007 past experiences. Particularly, a variable capturing the behaviour of Francois Bayrou’s voters has been included. From 2009 (Q1) up to 2011 (Q4), we have used the vote function in order to simulate the votes for the Left, the Right and the National Front, at the two rounds, asking ‘what would be the result of the vote if elections were held now’? Then we compare the vote simulations to the vote intention polls and we try to explain the differences between the two predicting methods. The Left and Francois Hollande are largely and continuously declared as the winners by the pollsters since 2009. On the contrary, the vote function simulations result in a final forecast giving Nicolas Sarkozy 50.6 per cent at the second round. Maintaining this slight advantage (while fixing Incumbent's popularity at a 32 per cent approval rate) requires the unemployment rate (U) not to exceed 9.6 per cent 4 months before the election date.

Accuracy of Vote Expectation Surveys in Forecasting Elections

Simple surveys that ask people who they expect to win are among the most accurate methods for forecasting U.S. presidential elections. The majority of respondents correctly predicted the election winner in 193 (89%) of 217 surveys conducted from 1932 to 2012. Across the last 100 days prior to the seven elections from 1988 to 2012, vote expectation surveys provided more accurate forecasts of election winners and vote shares than four established methods (vote intention polls, prediction markets, econometric models, and expert judgment). Gains in accuracy were particularly large compared to polls. On average, the error of expectation-based vote-share forecasts was 51% lower than the error of polls published the same day. Compared to prediction markets, vote expectation forecasts reduced the error on average by 6%. Vote expectation surveys are inexpensive, easy to conduct, and the results are easy to understand. They provide accurate and stable forecasts and thus make it difficult to frame elections as horse races. Vote expectation surveys should be more strongly utilized in the coverage of election campaigns.

Fuzzy min–max neural networks for categorical data: application to missing data imputation

The fuzzy min–max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min–max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data—the set of the respondents’ individual answers to the questions—of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes.

Citizen forecasting: Can UK voters see the future?

The leading approaches to election forecasting have been statistical models, prediction markets, or vote intention polls. This paper explores a different, little used approach – citizen forecasting – a method never yet tried for the case of the United Kingdom. Citizen forecasting simply asks voters in a scientific pre-election survey who they think will win. This aggregated (averaged) result is then assessed for its accuracy in forecasting the overall election outcome. This assessment is carried out on UK general elections from 1951 to 2005, and then applied to 2010. We find, among other things, that generally speaking the majority of the electorate can foretell the winner in advance.

By-election exit polls

With the rise of the Alliance parties, by-elections have become an important focus of the media’s coverage of the political scene in the UK. The television companies and newspapers regularly commission polls to predict the shares of the vote won by each party standing in the by-election. These polls take two forms: voting intention polls of the constituency electorate are carried out before polling day and so-called ‘exit’ polls on the election day itself when voters are interviewed as they leave the polling stations. In this paper we describe the statistical basis of the sampling scheme and estimation method developed for use by the BBC TV Newsnight programme in a series of ten byelection exit polls carried out in the period November 198 1 to May 1986. A new method of estimation of party shares of the vote, based on voter movements from the previous general election is described. This method is shown to perform generally better than the traditional method based on declared vote. It has potential application to the general problem of estimation of party shares from any type of voting intention poll. We first discuss the problems of carrying out by-election exit polls. The sampling scheme and estimation method developed are described in Section 2. Section 3 compares the performance of the voter transition method for the estimation of party shares with the traditional merhod and evaluates the contribution of the various components of the scheme to its success.